Safranski, T. J. | bioRxiv Science

bioRxiv2022

Can blood at adult age predict epigenetic changes of the brain during fetal stages?

Correspondence in DNA methylation between blood and brain is known in humans. If this pattern is present in pig has not been examined. In this study, we profiled DNA methylation of blood from pigs at adult ages, and compared those with the methylation profiles of fetal brain. Neural network regression modeling showed specific methylations in the adult blood that can reliably predict methylation of the fetal brain. Genes associated with these predictive methylations included markers of specific cell types of blood and brain, in particular, markers of bone marrow hematopoietic progenitors, and glial cells primarily the ependymal and Schwann cells of brain. The results of this study show that developmental methylation changes of the brain during fetal stages are maintained as an epigenetic memory in the blood in adult life. Thus, pig models may be harnessed to uncover potential roles of epigenetic memory in brain health and diseases.

genomics↗

bioRxiv2022

Analysis of polygenic selection in purebred and crossbred pig genomes using Generation Proxy Selection Mapping

BackgroundArtificial selection on quantitative traits using breeding values and selection indices in commercial livestock breeding populations causes changes in allele frequency over time, termed polygenic selection, at causal loci and the surrounding genomic regions. Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection mapping analyses. Here, we applied Generation Proxy Selection Mapping (GPSM), a genome-wide association analysis of SNP genotype (38,294 to 46,458 SNPs) of birth date, in four pig populations (15,457, 15,772, 16,595 and 8,447 pigs per population) to identify loci responding to artificial selection over a span of five to ten years. Gene-drop simulation analyses were conducted to validate GPSM results. Selection signatures within and across each population of pigs were compared in the context of commercial pork production. ResultsForty-nine to 854 loci were identified by GPSM as under selection (Q-values less than 0.10) across 15 subsets of pigs based on population combinations. The number of significant associations increased as populations of pigs were pooled. In addition, several significant associations were identified in more than one population. These results indicate concurrent selection objectives, similar genetic architectures, and shared causal variants responding to selection across populations. Negligible error rates (less than or equal to 0.02%) of false-positive associations were identified when testing GPSM on gene-drop simulated genotypes, suggesting that GPSM distinguishes selection from random genetic drift in actual pig populations. ConclusionsThis work confirms the efficacy and accuracy of the GPSM method in detecting selected loci in commercial pig populations. Our results suggest shared selection objectives and genetic architectures across swine populations. Identified polygenic selection highlights loci important to swine production.

genomics↗